Experience in fintech, payments, banking, marketplaces or another regulated or high-risk domain
Experience in AML, financial crime, sanctions, PEP screening, adverse media, fraud, trust and safety or transaction monitoring
Experience building or improving name screening or adverse media systems
Familiarity with modern LLM evaluation, prompt/model experimentation, retrieval quality assessment and AI observability
Experience applying graph analytics to detect mule networks, collusive behavior, coordinated account activity or interconnected high-risk entities
Experience developing proactive risk discovery capabilities rather than exclusively optimizing existing supervised models or rules
APPLICANT SAFETY POLICY: FRAUD AND THIRD-PARTY RECRUITERS
Airwallex does not accept unsolicited resumes from search firms/recruiters. Airwallex will not pay any fees to search firms/recruiters if a candidate is submitted by a search firm/recruiter unless an agreement has been entered into with respect to specific open position(s). Search firms/recruiters submitting resumes to Airwallex on an unsolicited basis shall be deemed to accept this condition, regardless of any other provision to the contrary
7+ years of experience in Data Science, Machine Learning, Applied AI, Risk Analytics, or a related quantitative field, with demonstrated impact at Staff, Lead, or equivalent scope
Strong expertise in applied machine learning and modern AI, with experience building and productionizing data-driven solutions at scale
Experience with one or more areas highly relevant to financial crime detection, such as NLP/LLMs, entity resolution, information retrieval, graph or network analytics, anomaly detection, or risk scoring
Strong SQL and Python skills are must
Strong communication and stakeholder management skills, with the ability to influence senior partners across Product, Engineering, Risk, Operations, and Compliance